Development of a capability-based scheduling heuristic for matrix production systems

Abstract The growing diversity of product variants, accelerated technology shifts, and shorter life cycles demand highly flexible and efficient production systems in the automotive industry. Matrix-based assembly systems offer a promising response by enabling modular workstation configurations and variant-specific task execution. A key challenge lies in designing such systems for optimized task-to-resource scheduling under fluctuating workloads and varying capability requirements. This paper presents a capability-based scheduling logic tailored for matrix production environments, which incorporates heuristic rules for task assignment under constraint-based planning conditions. The algorithm is formally described through a mathematical model that defines the objective function, constraints, and decision variables, supported by prioritization heuristics. To ensure transparency and reproducibility, the scheduling logic is also visualized in a Unified Modeling Language (UML) activity diagram. A case study using real-world data from the electric vehicle final assembly of a leading OEM validates the method. Results show notable improvements in station utilization and system adaptability compared to conventional line-based configurations. The proposed scheduling framework contributes to the development of agile and human-centered production control architectures, supporting the transition toward flexible, high-variant manufacturing.